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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: sentiment_roberta_large_with_diary
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# sentiment_roberta_large_with_diary
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This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5671
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- Micro f1 score: 80.0000
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- Auprc: 77.0282
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- Accuracy: 0.8
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Micro f1 score | Auprc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-------:|:--------:|
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| 1.6198 | 0.13 | 100 | 1.3872 | 48.9362 | 55.5743 | 0.4894 |
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| 0.6603 | 0.26 | 200 | 0.9249 | 65.9574 | 62.8759 | 0.6596 |
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| 0.5387 | 0.4 | 300 | 0.7262 | 73.1915 | 71.1936 | 0.7319 |
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| 0.4801 | 0.53 | 400 | 0.6623 | 74.0426 | 68.8606 | 0.7404 |
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| 0.4597 | 0.66 | 500 | 0.6092 | 76.1702 | 75.7346 | 0.7617 |
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| 0.4217 | 0.79 | 600 | 0.5929 | 78.7234 | 76.8709 | 0.7872 |
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| 0.4148 | 0.93 | 700 | 0.5671 | 80.0000 | 77.0282 | 0.8 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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